As technology has developed, the need for processing power has also increased. Cluster computing is a technique often employed to address this demand for increased processing power. In a computer cluster, multiple processors may be connected to each other to operate in parallel to perform coordinated operations. The connections may be made through hardware, networks, and/or software to cause the multiple processors in the cluster to function as a single system, working together to accomplish a programmed task. The multiple processors may be located in physical proximity to each other for ease of execution.
In a cluster application, each computing unit is referred to as a “node.” A node may be formed of a single processor or a processor set, to perform a particular task designated by a server. Cluster computing involves multiple servers coordinating tasks across multiple nodes. In doing so, cluster applications offer increased performance over the use of a single processor and are often employed in supercomputers for a wide range of computationally intensive tasks in the field of computational science.
Types of computer cluster models include load-balancing clusters, high-availability clusters, and high-performance clusters. A load-balancing cluster model allocates the number of users or transactions of a particular system across a plurality of nodes. This increases the efficiency and processing time of a server. In a high-availability cluster model, multiple servers interact with a plurality of nodes such that certain servers replicate the operations of other servers to allow continued processing in the event of failure of a single node in the computer cluster. A high-performance cluster model provides parallel data processing for data-intensive computing. In all cluster computer models, advantages may include increased cost efficiency achieved from reduced power consumption and speed compared to use of mainframe computers, increased processing speed, improved network infrastructure, and flexibility for upgrades and adding additional components to the system.
One of the obstacles associated with cluster applications is the limited availability of devices for mounting processors employed in cluster computing without impeding the above-mentioned advantages. Brackets are often used for mounting processors. However, difficulties are often encountered when using brackets for mounting processors for cluster applications, including excessive heat generation and limited access to interfaces on the processor.
A large number of component failures in clusters are heat-related. Thus, there is a demand for a bracket and cluster mount configuration that reduces heat-related failures in order to increase the overall reliability of the cluster.
Brackets currently available support individual processors horizontally. In such an arrangement, the major surface of the processor is generally parallel to a mounting surface, and in cluster configurations each processor is generally stacked on top of one another with limited space between each processor.
This arrangement exacerbates the problem of overheating and minimizes the ability to effectively cool the processors without complex cooling arrangements (e.g., using high air-flow fans, heat sinks, and even liquid-cooling). One challenge associated with cooling through the use of a fan is that the nearby space to which the hot air is forced may be occupied by other processors or even other clusters of processors. Conversely, a cluster may receive hot air discharged by the cooling fan of a nearby cluster. This reduces the overall effectiveness of the cooling system which often does not realize a net reduction of heat surrounding the cluster. Therefore a need exists for curing overheating-induced failures.
While brackets exist for supporting processors, such brackets may exhibit difficulty in supporting processors having a plurality of ports for interfacing with related devices. For example, Raspberry Pi is a low-cost, widely-used, single-board computer configured to accept a plurality of inputs including USB, MicroSD cards, Display Serial Interface, micro USB Power input, HDMI, Camera Serial Interface port, composite video and audio output jack, LAN port, GPIOs pins, etc. Existing brackets mount processors in pairs to a single bracket, often shielding an edge of the processor, which makes it difficult to access ports located on the processor and interface other hardware with the processor.
Existing brackets combined with the stacked cluster configuration described above limit user accessibility to an individual processor and also exacerbate the issue of the heat-induced failures. For example, a user may need to troubleshoot or replace a failed individual processor within the cluster. However, this may be difficult or impossible to do without disrupting the whole cluster, because the target processor may be supported in a dense field of other processors or may be secured to a bracket that is securing another processor. If the failed processor is not replaced, other processors in the cluster may experience a greater load and may generate more heat, leading to more system failures.
Therefore, a need exists for a bracket capable of reducing the number of heat-induced failures within a cluster, while facilitating cluster configurations in which the arrangement of individual processors does not impede a user's ability to easily access a targeted processor. The present disclosure is directed to addressing these and other challenges.